Security and Safety-Based Parking Area Monitoring System

Abstract

Security became a major concern these days in parking areas. Nowadays vehicles are rapidly increasing due to the rapid increase in parking traffic. Vehicle-safe parking has become a serious problem for organizations and Universities. Some vehicles do not register them legally or utilize the license plates of other vehicles. Those license plates can be used to determine the identification of a vehicle accused of committing a crime around the organization. So only detecting the number plate as the Vehicle identification at the parking entrance is not safe. For that proposing a novelty-based Smart Parking Area Monitoring System to overcome this problem. Here, train the vehicle model using the neural network transfer learning technique to identify the vehicle model and classify the vehicles. The entrance of the organization detects and compares the vehicle models with number plate details and operates the barrier system based on the vehicle’s authorization status. Nowadays parking systems detect wrong-parked vehicles using sensors in every parking slot. It is very costly and not efficiently working. This research proposes a wrong parking detection system by using only the CCTV cameras of parking areas. Here using Yolo object detection and OpenCV line detection algorithms to detect parking slots and wrong-parked vehicles.